Overview

Dataset statistics

Number of variables6
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory54.6 B

Variable types

Numeric3
Categorical1
Text2

Dataset

Description충청남도개발공사 행복주택(임대주택) 사업별 분양현황(분양률) 공개하여 도민들의 행복주택 사업에 대한 청약정보를 손쉽게 확인할수 있도록 정보 제공
URLhttps://www.data.go.kr/data/15106735/fileData.do

Alerts

순번 is highly overall correlated with 지역단지High correlation
공급세대 is highly overall correlated with 청약세대High correlation
청약세대 is highly overall correlated with 공급세대High correlation
지역단지 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:31:09.248521
Analysis finished2023-12-12 12:31:10.568531
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:31:10.649940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2023-12-12T21:31:10.840168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

지역단지
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
행복주택 아산배방
7 
행복주택 홍성내포
7 
행복주택 예산주교
6 
아트빌리지
5 
행복주택 천안남산
3 
Other values (4)
9 

Length

Max length9
Median length9
Mean length8.1351351
Min length3

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st row행복주택 아산배방
2nd row행복주택 아산배방
3rd row행복주택 아산배방
4th row행복주택 아산배방
5th row행복주택 아산배방

Common Values

ValueCountFrequency (%)
행복주택 아산배방 7
18.9%
행복주택 홍성내포 7
18.9%
행복주택 예산주교 6
16.2%
아트빌리지 5
13.5%
행복주택 천안남산 3
8.1%
행복주택 서천군사 3
8.1%
행복주택 당진채운 3
8.1%
매입형 2
 
5.4%
공주덕성그린시티빌 1
 
2.7%

Length

2023-12-12T21:31:11.061731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:31:11.283040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행복주택 29
43.9%
아산배방 7
 
10.6%
홍성내포 7
 
10.6%
예산주교 6
 
9.1%
아트빌리지 5
 
7.6%
천안남산 3
 
4.5%
서천군사 3
 
4.5%
당진채운 3
 
4.5%
매입형 2
 
3.0%
공주덕성그린시티빌 1
 
1.5%

주택타입
Text

Distinct27
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T21:31:11.558708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5
Min length3

Characters and Unicode

Total characters185
Distinct characters22
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)64.9%

Sample

1st row36㎡
2nd row44㎡
3rd row59㎡A
4th row59㎡B
5th row59㎡C
ValueCountFrequency (%)
59㎡ 5
 
13.5%
36㎡ 4
 
10.8%
44㎡ 4
 
10.8%
59b(rl8 1
 
2.7%
b형(140㎡ 1
 
2.7%
a3(120㎡ 1
 
2.7%
a2(140㎡ 1
 
2.7%
a1(130㎡ 1
 
2.7%
35㎡ 1
 
2.7%
73㎡ 1
 
2.7%
Other values (17) 17
45.9%
2023-12-12T21:31:12.006896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 30
16.2%
4 21
11.4%
9 17
9.2%
5 14
 
7.6%
3 12
 
6.5%
( 12
 
6.5%
) 12
 
6.5%
A 11
 
5.9%
6 8
 
4.3%
1 8
 
4.3%
Other values (12) 40
21.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
49.2%
Uppercase Letter 36
 
19.5%
Other Symbol 30
 
16.2%
Open Punctuation 12
 
6.5%
Close Punctuation 12
 
6.5%
Dash Punctuation 2
 
1.1%
Other Letter 2
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 21
23.1%
9 17
18.7%
5 14
15.4%
3 12
13.2%
6 8
 
8.8%
1 8
 
8.8%
0 5
 
5.5%
8 3
 
3.3%
2 2
 
2.2%
7 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
A 11
30.6%
B 7
19.4%
L 7
19.4%
R 7
19.4%
C 2
 
5.6%
D 1
 
2.8%
E 1
 
2.8%
Other Symbol
ValueCountFrequency (%)
㎡ 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Letter
ValueCountFrequency (%)
형 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 147
79.5%
Latin 36
 
19.5%
Hangul 2
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 30
20.4%
4 21
14.3%
9 17
11.6%
5 14
9.5%
3 12
 
8.2%
( 12
 
8.2%
) 12
 
8.2%
6 8
 
5.4%
1 8
 
5.4%
0 5
 
3.4%
Other values (4) 8
 
5.4%
Latin
ValueCountFrequency (%)
A 11
30.6%
B 7
19.4%
L 7
19.4%
R 7
19.4%
C 2
 
5.6%
D 1
 
2.8%
E 1
 
2.8%
Hangul
ValueCountFrequency (%)
형 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 153
82.7%
CJK Compat 30
 
16.2%
Hangul 2
 
1.1%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 30
100.0%
ASCII
ValueCountFrequency (%)
4 21
13.7%
9 17
11.1%
5 14
9.2%
3 12
 
7.8%
( 12
 
7.8%
) 12
 
7.8%
A 11
 
7.2%
6 8
 
5.2%
1 8
 
5.2%
B 7
 
4.6%
Other values (10) 31
20.3%
Hangul
ValueCountFrequency (%)
형 2
100.0%

공급세대
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)64.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.459459
Minimum1
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:31:12.188532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q15
median11
Q324
95-th percentile102.2
Maximum180
Range179
Interquartile range (IQR)19

Descriptive statistics

Standard deviation41.230109
Coefficient of variation (CV)1.558237
Kurtosis7.7530421
Mean26.459459
Median Absolute Deviation (MAD)6
Skewness2.7662843
Sum979
Variance1699.9219
MonotonicityNot monotonic
2023-12-12T21:31:12.361415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
5 6
16.2%
16 3
 
8.1%
8 3
 
8.1%
60 2
 
5.4%
17 2
 
5.4%
4 2
 
5.4%
3 2
 
5.4%
6 1
 
2.7%
1 1
 
2.7%
2 1
 
2.7%
Other values (14) 14
37.8%
ValueCountFrequency (%)
1 1
 
2.7%
2 1
 
2.7%
3 2
 
5.4%
4 2
 
5.4%
5 6
16.2%
6 1
 
2.7%
7 1
 
2.7%
8 3
8.1%
10 1
 
2.7%
11 1
 
2.7%
ValueCountFrequency (%)
180 1
2.7%
167 1
2.7%
86 1
2.7%
74 1
2.7%
60 2
5.4%
45 1
2.7%
30 1
2.7%
25 1
2.7%
24 1
2.7%
17 2
5.4%

청약세대
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.405405
Minimum1
Maximum605
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:31:12.548865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.8
Q14
median24
Q365
95-th percentile313.8
Maximum605
Range604
Interquartile range (IQR)61

Descriptive statistics

Standard deviation128.63503
Coefficient of variation (CV)1.8533863
Kurtosis9.0550973
Mean69.405405
Median Absolute Deviation (MAD)20
Skewness2.9480858
Sum2568
Variance16546.97
MonotonicityNot monotonic
2023-12-12T21:31:12.713654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2 4
 
10.8%
4 3
 
8.1%
25 2
 
5.4%
19 2
 
5.4%
1 2
 
5.4%
103 1
 
2.7%
16 1
 
2.7%
8 1
 
2.7%
64 1
 
2.7%
44 1
 
2.7%
Other values (19) 19
51.4%
ValueCountFrequency (%)
1 2
5.4%
2 4
10.8%
3 1
 
2.7%
4 3
8.1%
5 1
 
2.7%
7 1
 
2.7%
8 1
 
2.7%
11 1
 
2.7%
16 1
 
2.7%
19 2
5.4%
ValueCountFrequency (%)
605 1
2.7%
425 1
2.7%
286 1
2.7%
280 1
2.7%
151 1
2.7%
103 1
2.7%
80 1
2.7%
71 1
2.7%
68 1
2.7%
65 1
2.7%

청약률_퍼센트
Text

Distinct33
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T21:31:12.900980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.8918919
Min length2

Characters and Unicode

Total characters144
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)86.5%

Sample

1st row171.7
2nd row36.1
3rd row574.3
4th row362.3
5th row156.3
ValueCountFrequency (%)
100 5
 
13.5%
66.7 1
 
2.7%
256 1
 
2.7%
1467 1
 
2.7%
1682 1
 
2.7%
133.3 1
 
2.7%
6.7 1
 
2.7%
290 1
 
2.7%
157.8 1
 
2.7%
43.8 1
 
2.7%
Other values (23) 23
62.2%
2023-12-12T21:31:13.318864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 21
14.6%
0 19
13.2%
. 19
13.2%
1 18
12.5%
5 13
9.0%
2 13
9.0%
6 11
7.6%
7 11
7.6%
8 10
6.9%
4 6
 
4.2%
Other values (2) 3
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123
85.4%
Other Punctuation 21
 
14.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 21
17.1%
0 19
15.4%
1 18
14.6%
5 13
10.6%
2 13
10.6%
6 11
8.9%
7 11
8.9%
8 10
8.1%
4 6
 
4.9%
9 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 19
90.5%
% 2
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
Common 144
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 21
14.6%
0 19
13.2%
. 19
13.2%
1 18
12.5%
5 13
9.0%
2 13
9.0%
6 11
7.6%
7 11
7.6%
8 10
6.9%
4 6
 
4.2%
Other values (2) 3
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 21
14.6%
0 19
13.2%
. 19
13.2%
1 18
12.5%
5 13
9.0%
2 13
9.0%
6 11
7.6%
7 11
7.6%
8 10
6.9%
4 6
 
4.2%
Other values (2) 3
 
2.1%

Interactions

2023-12-12T21:31:09.997329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:09.469083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:09.717452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:10.088645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:09.553345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:09.805387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:10.206196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:09.636359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:09.899143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:31:13.435984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지역단지주택타입공급세대청약세대청약률_퍼센트
순번1.0000.9090.0000.4250.1890.970
지역단지0.9091.0000.0000.4640.1961.000
주택타입0.0000.0001.0000.0000.0000.000
공급세대0.4250.4640.0001.0000.9021.000
청약세대0.1890.1960.0000.9021.0001.000
청약률_퍼센트0.9701.0000.0001.0001.0001.000
2023-12-12T21:31:13.559721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번공급세대청약세대지역단지
순번1.000-0.466-0.4150.698
공급세대-0.4661.0000.7060.224
청약세대-0.4150.7061.0000.043
지역단지0.6980.2240.0431.000

Missing values

2023-12-12T21:31:10.383659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:31:10.516080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

순번지역단지주택타입공급세대청약세대청약률_퍼센트
01행복주택 아산배방36㎡60103171.7
12행복주택 아산배방44㎡1806536.1
23행복주택 아산배방59㎡A74425574.3
34행복주택 아산배방59㎡B167605362.3
45행복주택 아산배방59㎡C1625156.3
56행복주택 아산배방59㎡D1727158.8
67행복주택 아산배방59㎡E86280325.6
78행복주택 홍성내포36A(RL9)521420
89행복주택 홍성내포36B(RL9)519380
910행복주택 홍성내포44A(RL9)5240
순번지역단지주택타입공급세대청약세대청약률_퍼센트
2728행복주택 당진채운44㎡3026.7
2829행복주택 당진채운59㎡6080133.3
2930매입형59㎡172861682%
3031매입형73㎡3441467%
3132공주덕성그린시티빌35㎡2564256
3233아트빌리지A1(130㎡)88100
3334아트빌리지A2(140㎡)44100
3435아트빌리지A3(120㎡)22100
3536아트빌리지B형(140㎡)44100
3637아트빌리지C형(140㎡)11100